Amazon SageMaker
Developer Guide

Log Amazon SageMaker Events with Amazon CloudWatch

To help you debug your training jobs, endpoints, transform jobs, notebook instances, and notebook instance lifecycle configurations, anything an algorithm container, a model container, or a notebook instance lifecycle configuration sends to stdout or stderr is also sent to Amazon CloudWatch Logs. In addition to debugging, you can use these for progress analysis.

Logs

The following table lists all of the logs provided by Amazon SageMaker.

Logs

Log Group Name Log Stream Name
/aws/sagemaker/TrainingJobs

[training-job-name]/algo-[instance-number-in-cluster]-[epoch_timestamp]

/aws/sagemaker/Endpoints/[EndpointName]

[production-variant-name]/[instance-id]

[production-variant-name]/[instance-id]/[container-name provided in SageMaker model] (For Inference Pipelines)

/aws/sagemaker/NotebookInstances

[notebook-instance-name]/[LifecycleConfigHook]

[notebook-instance-name]/jupyter.log

/aws/sagemaker/TransformJobs

[transform-job-name]/[instance-id]-[epoch_timestamp]

[transform-job-name]/[instance-id]-[epoch_timestamp]/data-log

[transform-job-name]/[instance-id]-[epoch_timestamp]/[container-name provided in SageMaker model] (For Inference Pipelines)

/aws/sagemaker/LabelingJobs

[labeling-job-name]

/aws/sagemaker/groundtruth/WorkerActivity

aws/sagemaker/groundtruth/worker-activity/[requester-AWS-Id]-[region]/[timestamp]

Note

1. The /aws/sagemaker/NotebookInstances/[LifecycleConfigHook] log stream is created when you create a notebook instance with a lifecycle configuration. For more information, see Customize a Notebook Instance .

2. For Inference Pipelines, if you don't provide container names, the platform uses **container-1, container-2**, and so on, corresponding to the order provided in the Amazon SageMaker model.

For more information about logging events with CloudWatch logging, see What is Amazon CloudWatch Logs? in the Amazon CloudWatch User Guide.